U.S. patent application number 17/209403 was filed with the patent office on 2022-09-29 for distributed and realtime smart data collection and processing in mobile networks.
This patent application is currently assigned to AT&T Intellectual Property I, L.P.. The applicant listed for this patent is AT&T Intellectual Property I, L.P.. Invention is credited to Satyendra Gurjar, Baofeng Jiang, Mehdi Malboubi.
Application Number | 20220312183 17/209403 |
Document ID | / |
Family ID | 1000005563524 |
Filed Date | 2022-09-29 |
United States Patent
Application |
20220312183 |
Kind Code |
A1 |
Malboubi; Mehdi ; et
al. |
September 29, 2022 |
DISTRIBUTED AND REALTIME SMART DATA COLLECTION AND PROCESSING IN
MOBILE NETWORKS
Abstract
Aspects of the subject disclosure may include, for example, a
device in which a processing system instantiates a data collector
agent at an edge of a communication network. The data collector
agent determines a type of data to be collected for executing an
application, determines a data collection procedure including a
data collection algorithm selected in accordance with the
application, and performs the data collection procedure, resulting
in collected data. The system can also configure a data processing
module to process the collected data in accordance with the
application; the data processing module is connected to the data
collector agent and a database, and includes a data streaming
system. The system can also configure a monitoring module connected
to the controller for monitoring performance of the data processing
module and a status of the database, and store the collected data
in near real time. Other embodiments are disclosed.
Inventors: |
Malboubi; Mehdi; (San Ramon,
CA) ; Jiang; Baofeng; (Pleasanton, CA) ;
Gurjar; Satyendra; (Milford, CT) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
AT&T Intellectual Property I, L.P. |
Atlanta |
GA |
US |
|
|
Assignee: |
AT&T Intellectual Property I,
L.P.
Atlanta
GA
|
Family ID: |
1000005563524 |
Appl. No.: |
17/209403 |
Filed: |
March 23, 2021 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04W 24/10 20130101;
H04W 4/025 20130101; H04W 24/08 20130101; H04W 8/18 20130101; H04W
4/20 20130101; G06N 20/00 20190101 |
International
Class: |
H04W 8/18 20060101
H04W008/18; H04W 4/02 20060101 H04W004/02; H04W 4/20 20060101
H04W004/20; H04W 24/08 20060101 H04W024/08; H04W 24/10 20060101
H04W024/10; G06N 20/00 20060101 G06N020/00 |
Claims
1. A device, comprising: a processing system including a processor
of a controller, the processing system being connected to a
communication network; and a memory that stores executable
instructions that, when executed by the processing system,
facilitate performance of operations, the operations comprising:
instantiating a data collector agent at a network edge of the
communication network, wherein the data collector agent determines
a type of data to be collected for executing an application,
determines a data collection procedure including a data collection
algorithm selected in accordance with the application, and performs
the data collection procedure, resulting in collected data, wherein
the data collection procedure comprises selecting, from a set of
data items available to the data collector agent, a subset of the
data items; configuring a data processing module to process the
collected data in accordance with the application, wherein the data
processing module is connected to the data collector agent and to a
database, wherein the data processing module comprises a data
streaming system; configuring a monitoring module connected to the
controller for monitoring performance of the data processing module
and a status of the database; and storing the collected data at the
database in near real time, wherein the database is accessible via
a web server to a user device communicating on the network.
2. The device of claim 1, wherein the operations further comprise
instantiating an additional physical or virtual data collector
agent at a regional data center of the network.
3. The device of claim 1, wherein the data collection algorithm
comprises a machine learning/artificial intelligence (ML/AI)
algorithm.
4. The device of claim 3, wherein the operations further comprise
training the ML/AI algorithm.
5. The device of claim 1, wherein in accordance with the
application, each of the subset of the data items is measured by
the data collector agent, resulting in a set of known entries of a
matrix, the matrix including the set of known entries and a set of
unknown entries, and wherein each of the set of unknown entries is
estimated using an ML/AI algorithm.
6. The device of claim 1, wherein the set of data items corresponds
to a matrix, wherein the data collector agent constructs a new
matrix approximating the matrix, the new matrix including first
elements corresponding to the subset of the data items, and wherein
the new matrix comprises the collected data.
7. The device of claim 6, wherein the new matrix comprises second
elements generated using a matrix completion algorithm.
8. The device of claim 1, wherein the user device accesses the web
server using a portal, a graphical user interface (GUI), or a
combination thereof.
9. The device of claim 1, wherein the communication network
comprises a software-defined network, and wherein the operations
further comprise configuring the software-defined network.
10. The device of claim 1, wherein the communication network
comprises a plurality of cells, wherein the application comprises
predicting a key performance indicator (KPI) of interest on the
communication network, and wherein the data collection procedure is
performed for each cell of the plurality of cells experiencing the
KPI of interest exceeding a threshold.
11. The device of claim 1, wherein the application comprises
predicting locations of a plurality of user devices using key
performance indicators (KPIs), the KPIs including a signal strength
of a signal received from each of the plurality of user devices,
and wherein the data collection algorithm comprises a machine
learning/artificial intelligence (ML/AI) algorithm.
12. The device of claim 11, wherein the operations further comprise
training the ML/AI algorithm using location data of selected user
devices of the plurality of user devices.
13. A method comprising: instantiating, by a processing system
including a processor, a data collector agent at a network edge of
a communication network, wherein the data collector agent
determines a type of data to be collected for executing an
application, determines a data collection procedure including a
data collection algorithm selected in accordance with the
application, and performs the data collection procedure, resulting
in collected data, wherein the processing system comprises a
controller connected to the communication network, wherein the data
collection procedure comprises selecting, from a set of data items
available to the data collector agent, a subset of the data items,
the data items corresponding to signals from devices communicating
on the communication network; configuring, by the processing
system, a data processing module to process the collected data in
accordance with the application, wherein the data processing module
is connected to the data collector agent and to a database, wherein
the data processing module comprises a data streaming system;
configuring, by the processing system, a monitoring module
connected to the controller for monitoring performance of the data
processing module and a status of the database; and storing, by the
processing system, the collected data at the database in near real
time, wherein the database is accessible via a web server to a user
device communicating on the network.
14. The method of claim 13, wherein the data collection algorithm
comprises a machine learning/artificial intelligence (ML/AI)
algorithm.
15. The method of claim 13, wherein in accordance with the
application, each of the subset of the data items is measured by
the data collector agent, resulting in a set of known entries of a
matrix, the matrix including the set of known entries and a set of
unknown entries, and wherein each of the set of unknown entries is
estimated using an ML/AI algorithm.
16. The method of claim 13, wherein the set of data items
corresponds to a matrix, wherein the data collector agent
constructs a new matrix approximating the matrix, the new matrix
including first elements corresponding to the subset of the data
items, and wherein the new matrix comprises the collected data.
17. The method of claim 16, wherein the new matrix comprises second
elements generated using a matrix completion algorithm.
18. A non-transitory machine-readable medium comprising executable
instructions that, when executed by a processing system including a
processor of a controller, facilitate performance of operations
comprising: instantiating a data collector agent at a network edge
of a communication network, wherein the data collector agent
determines a type of data to be collected for executing an
application, determines a data collection procedure including a
data collection algorithm selected in accordance with the
application, and performs the data collection procedure, resulting
in collected data, wherein the data collection procedure comprises
selecting, from a set of data items available to the data collector
agent, a subset of the data items; configuring a data processing
module to process the collected data in accordance with the
application, wherein the data processing module is connected to the
data collector agent and to a database, wherein the data processing
module comprises a data streaming system; configuring a monitoring
module connected to the controller for monitoring performance of
the data processing module and a status of the database; and
storing the collected data at the database in near real time,
wherein the database is accessible to a user device communicating
on the network.
19. The non-transitory machine-readable medium of claim 18, wherein
the data collection algorithm comprises a machine
learning/artificial intelligence (ML/AI) algorithm.
20. The non-transitory machine-readable medium of claim 18, wherein
the set of data items corresponds to a matrix, wherein the data
collector agent constructs a new matrix approximating the matrix
and comprising the collected data, the new matrix including first
elements corresponding to the subset of the data items and second
elements generated using a matrix completion algorithm.
Description
FIELD OF THE DISCLOSURE
[0001] The subject disclosure relates to management of mobile
communication networks, and more particularly to providing
centralized access to network data in near real-time.
BACKGROUND
[0002] Access to centralized network information can be of critical
importance for many applications in mobile wireless networks.
Current approaches to build a centralized database can result in
high latency and high drop rates, which can cause significant
degradation of quality of service (QoS) for customers. In addition,
large-scale networks generally must contend with a large volume of
highly redundant data in space and time. Collecting, storing and
processing such a volume of data can be costly and burdensome in
many applications.
BRIEF DESCRIPTION OF THE DRAWINGS
[0003] Reference will now be made to the accompanying drawings,
which are not necessarily drawn to scale, and wherein:
[0004] FIG. 1 is a block diagram illustrating an exemplary,
non-limiting embodiment of a communications network in accordance
with various aspects described herein.
[0005] FIG. 2A is a block diagram illustrating an example,
non-limiting embodiment of a system for distributed and real-time
smart data collection, functioning within the communication network
of FIG. 1 in accordance with various aspects described herein.
[0006] FIG. 2B depicts an illustrative embodiment of a procedure
for cell traffic prediction, in accordance with various aspects
described herein.
[0007] FIG. 2C schematically illustrates a cell load traffic matrix
in accordance with embodiments of the disclosure.
[0008] FIG. 2D depicts an illustrative embodiment of a procedure
for predicting user equipment locations, in accordance with various
aspects described herein.
[0009] FIG. 2E depicts an illustrative embodiment of a method in
accordance with various aspects described herein.
[0010] FIG. 3 is a block diagram illustrating an example,
non-limiting embodiment of a virtualized communication network in
accordance with various aspects described herein.
[0011] FIG. 4 is a block diagram of an example, non-limiting
embodiment of a computing environment in accordance with various
aspects described herein.
[0012] FIG. 5 is a block diagram of an example, non-limiting
embodiment of a mobile network platform in accordance with various
aspects described herein.
[0013] FIG. 6 is a block diagram of an example, non-limiting
embodiment of a communication device in accordance with various
aspects described herein.
DETAILED DESCRIPTION
[0014] The subject disclosure describes, among other things,
illustrative embodiments for a smart and scalable platform for
collecting, processing and storing network data, using an
intelligent data collection algorithm that facilitates processing
and storing data in near real time. Other embodiments are described
in the subject disclosure.
[0015] One or more aspects of the subject disclosure include a
device that comprises a processing system and a memory; the
processing system includes a processor of a controller and is
connected to a communication network, and the memory stores
executable instructions that, when executed by the processing
system, facilitate performance of operations. The operations
include instantiating a data collector agent at a network edge of
the communication network. The data collector agent determines a
type of data to be collected for executing an application,
determines a data collection procedure including a data collection
algorithm selected in accordance with the application, and performs
the data collection procedure, resulting in collected data; the
data collection procedure comprises selecting a subset from a set
of data items available to the data collector agent. The operations
also include configuring a data processing module to process the
collected data in accordance with the application; the data
processing module is connected to the data collector agent and to a
database, and comprises a data streaming system. The operations
further include configuring a monitoring module connected to the
controller for monitoring performance of the data processing module
and a status of the database, and storing the collected data at the
database in near real time. The database is accessible via a web
server to a user device communicating on the network, so that the
user can interact with the system and its components on the
network.
[0016] One or more aspects of the subject disclosure include a
method that includes instantiating, by a processing system
including a processor, a data collector agent at a network edge of
a communication network. The data collector agent determines a type
of data to be collected for executing an application, determines a
data collection procedure including a data collection algorithm
selected in accordance with the application, and performs the data
collection procedure, resulting in collected data. The processing
system comprises a controller connected to the communication
network; the data collection procedure comprises selecting, from a
set of data items available to the data collector agent, a subset
of the data items; the data items correspond to signals from
devices communicating on the communication network. The method also
includes configuring, by the processing system, a data processing
module to process the collected data in accordance with the
application; the data processing module is connected to the data
collector agent and to a database, and the data processing module
comprises a data streaming system. The method further includes
configuring, by the processing system, a monitoring module
connected to the controller for monitoring performance of the data
processing module and a status of the database; and storing, by the
processing system, the collected data at the database in near real
time, the database being accessible via a web server to a user
device communicating on the network.
[0017] One or more aspects of the subject disclosure include a
non-transitory machine-readable medium comprising executable
instructions that, when executed by a processing system including a
processor of a controller, facilitate performance of operations.
The operations comprise instantiating a data collector agent at a
network edge of a communication network; the data collector agent
determines a type of data to be collected for executing an
application, determines a data collection procedure including a
data collection algorithm selected in accordance with the
application, and performs the data collection procedure, resulting
in collected data. The data collection procedure comprises
selecting, from a set of data items available to the data collector
agent, a subset of the data items. The operations also comprise
configuring a data processing module to process the collected data
in accordance with the application; the data processing module is
connected to the data collector agent and to a database, and
comprises a data streaming system, The operations further comprise
configuring a monitoring module connected to the controller for
monitoring performance of the data processing module and a status
of the database, and storing the collected data at the database in
near real time; the database is accessible to a user device
communicating on the network.
[0018] Referring now to FIG. 1, a block diagram is shown
illustrating an example, non-limiting embodiment of a system 100 in
accordance with various aspects described herein. For example,
system 100 can facilitate in whole or in part instantiating a data
collector agent at a network edge of the communication network. The
data collector agent determines a type of data to be collected for
executing an application, determines a data collection procedure
including a data collection algorithm selected in accordance with
the application, and performs the data collection procedure,
resulting in collected data; the data collection procedure
comprises selecting a subset from a set of data items available to
the data collector agent. In particular, a communications network
125 is presented for providing broadband access 110 to a plurality
of data terminals 114 via access terminal 112, wireless access 120
to a plurality of mobile devices 124 and vehicle 126 via base
station or access point 122, voice access 130 to a plurality of
telephony devices 134, via switching device 132 and/or media access
140 to a plurality of audio/video display devices 144 via media
terminal 142. In addition, communication network 125 is coupled to
one or more content sources 175 of audio, video, graphics, text
and/or other media. While broadband access 110, wireless access
120, voice access 130 and media access 140 are shown separately,
one or more of these forms of access can be combined to provide
multiple access services to a single client device (e.g., mobile
devices 124 can receive media content via media terminal 142, data
terminal 114 can be provided voice access via switching device 132,
and so on).
[0019] The communications network 125 includes a plurality of
network elements (NE) 150, 152, 154, 156, etc. for facilitating the
broadband access 110, wireless access 120, voice access 130, media
access 140 and/or the distribution of content from content sources
175. The communications network 125 can include a circuit switched
or packet switched network, a voice over Internet protocol (VoIP)
network, Internet protocol (IP) network, a cable network, a passive
or active optical network, a 4G, 5G, or higher generation wireless
access network, WIMAX network, UltraWideband network, personal area
network or other wireless access network, a broadcast satellite
network and/or other communications network.
[0020] In various embodiments, the access terminal 112 can include
a digital subscriber line access multiplexer (DSLAM), cable modem
termination system (CMTS), optical line terminal (OLT) and/or other
access terminal. The data terminals 114 can include personal
computers, laptop computers, netbook computers, tablets or other
computing devices along with digital subscriber line (DSL) modems,
data over coax service interface specification (DOCSIS) modems or
other cable modems, a wireless modem such as a 4G, 5G, or higher
generation modem, an optical modem and/or other access devices.
[0021] In various embodiments, the base station or access point 122
can include a 4G, 5G, or higher generation base station, an access
point that operates via an 802.11 standard such as 802.11n,
802.11ac or other wireless access terminal. The mobile devices 124
can include mobile phones, e-readers, tablets, phablets, wireless
modems, and/or other mobile computing devices.
[0022] In various embodiments, the switching device 132 can include
a private branch exchange or central office switch, a media
services gateway, VoIP gateway or other gateway device and/or other
switching device. The telephony devices 134 can include traditional
telephones (with or without a terminal adapter), VoIP telephones
and/or other telephony devices.
[0023] In various embodiments, the media terminal 142 can include a
cable head-end or other TV head-end, a satellite receiver, gateway
or other media terminal 142. The display devices 144 can include
televisions with or without a set top box, personal computers
and/or other display devices.
[0024] In various embodiments, the content sources 175 include
broadcast television and radio sources, video on demand platforms
and streaming video and audio services platforms, one or more
content data networks, data servers, web servers and other content
servers, and/or other sources of media.
[0025] In various embodiments, the communications network 125 can
include wired, optical and/or wireless links and the network
elements 150, 152, 154, 156, etc. can include service switching
points, signal transfer points, service control points, network
gateways, media distribution hubs, servers, firewalls, routers,
edge devices, switches and other network nodes for routing and
controlling communications traffic over wired, optical and wireless
links as part of the Internet and other public networks as well as
one or more private networks, for managing subscriber access, for
billing and network management and for supporting other network
functions.
[0026] FIG. 2A is a block diagram illustrating an example,
non-limiting embodiment of a system 201 for distributed and
real-time smart data collection, in accordance with various aspects
described herein. System 201 can be implemented with various types
of networks, including LTE and 5G networks. In this embodiment, a
processing system 2101 is connected to a mobile communication
network 2301 with eNB or gNB network nodes 2303 and a mobile
management entity (MME) 2302.
[0027] Processing system 2101 includes multiple modules, including
several controller-collector agents 2102 and a controller 2103. As
shown in FIG. 2A, the controller-collector agents (also referred to
herein as agents) are placed at various regional data centers and
network edge locations. The agents 2102 perform monitoring 2104 of
the status of data transfers, and determine what (and from which
users) information should be collected and/or transferred at a
given time for a particular application.
[0028] The controller 2103 receives and processes the monitoring
data to assess the available resources of the system and the
overall health of the system. In this embodiment, the controller
2103 can instantiate physical and/or virtual agents at the regional
data centers and network edges. The controller 2103 can also
configure sub-modules 2105 for data processing and data streaming.
In an embodiment, the controller can configure a distributed
streaming platform (using, for example, partitions and topics in
Kafka.RTM.). In a further embodiment, the controller can configure
underlying software and data routing in a software defined network
(SDN), to improve network performance (for example, reducing
latency and/or increasing throughput).
[0029] In this embodiment, the agents 2102 are configured to
collect the most informative data for a particular application.
Each agent 2102 includes an intelligent data collection algorithm
to determine the procedure for collecting data for each
application. Alternatively, one or more data collection algorithms
may be at a central location and accessible to the various agents,
based on the application.
[0030] In a particular embodiment, the agents 2102 determine the
data collection procedure using machine learning and/or artificial
intelligence (ML/AI) algorithms installed on, or accessible to, the
agents.
[0031] The collected data are processed by the data
processing/streaming subsystems 2105 and stored in one or more
databases 2106 in near real-time. As shown schematically in FIG.
2A, realtime database 2106 may include multiple data storage units
2108. In an embodiment, the collected data is stored in a
centralized realtime database 2110 separate from the processing
system 2101. In various embodiments, internal and external users
can access, and interact with, the processed centralized data via a
web server 2115, by utilizing a portal 2201 or graphical user
interface (GUI) 2202. As shown schematically in FIG. 2A, web server
2115 may include multiple processors 2116. In additional
embodiments, internal and external users can access other internal
data sources 2112 or external data sources 2113.
[0032] It will be appreciated that system 201 may comprise a
platform including a cluster of network nodes, implemented on a
cluster of servers; accordingly, the system is easily scalable
since the controller can add nodes when necessary. In various
embodiments, system 201 can provide capabilities including: (1)
distributed data collection and processing/streaming with
scalability; (2) centralized access to information in near
real-time with low latency and high reliability, with a low drop
rate; (3) smart data collection over space and time (i.e.,
depending on the application, the most informative data are
measured and collected in a distributed manner at an optimal time
and place).
[0033] In addition, it will be appreciated that system 201 may be
implemented on other networks, including future networks, and with
various components of those networks.
[0034] FIG. 2B depicts a procedure 202 for predicting traffic in a
cellular network, in accordance with various aspects of the
disclosure. In an embodiment, agents 2102 are instantiated at
regional data centers and/or network edge locations, and are
configured to collect the most informative data relating to cell
traffic. In this embodiment, each agent includes a data collection
algorithm; the data collection algorithm determines procedures for
collecting data for a specific application. In general, network
data have substantial spatial-temporal redundancy; accordingly, the
data collection algorithm can measure and/or collect a subset of
the overall data that includes the most informative data for the
specific application. Based on the application, one or more
different ML/AI algorithms (or a combination of algorithms) can be
used, including random sampling, multi-armed bandit algorithms,
heuristic algorithms (e.g. genetic algorithm), reinforcement
learning algorithms and deep-learning algorithms.
[0035] In accordance with the data collection algorithm, an agent
monitors cell traffic (step 220); a traffic volume threshold may be
established, below which traffic data is not collected. The agent
determines the subset of data that needs to be collected at that
specific time (step 222), and collects that data according to the
algorithm (step 224).
[0036] In this embodiment, the traffic load data for a cellular
network can be expressed as a matrix; the entries of a subset of
the matrix are measured and used to estimate/predict unknown
entries of the cell traffic matrix. This subset is used by a matrix
completion algorithm to construct a close approximation of the
original matrix (step 226). A cell traffic prediction procedure is
then performed (step 228), using the approximate matrix.
[0037] FIG. 2C is a schematic illustration 203 of a cell traffic
load matrix used to predict cell traffic, in accordance with
embodiments of the disclosure. Cell traffic load is an example of a
key performance indicator (KPI) that may be of interest and that
can be estimated and/or predicted; examples of other KPIs include
utilization, retainability and accessibility of cells or a group of
cells. Matrix X has elements 230 with traffic load data for a group
of M cells, measured at N points in time. Instead of using all
historical data in a traffic prediction procedure, a subset of
matrix X is sampled by the controller-collector agents for use in
the prediction. Matrix elements 231, where the data is
measured/collected according to a data collection/sampling
algorithm (e.g., random sampling, multi-armed bandit algorithms,
heuristic algorithms, reinforcement learning algorithms) are marked
"x" in FIG. 2C. The other elements 232 marked "o" can be estimated
using matrix completion algorithms or deep learning algorithms (or
a combination of algorithms).
[0038] FIG. 2D depicts a procedure 204 for predicting user
equipment (UE) locations, in accordance with various aspects of the
disclosure. In an embodiment, a ML/AI model is used to predict the
location of a UE, based on a received signal strength from the UE
and other KPIs such as reference signal received quality (RSQ) and
channel quality index (CQI). In general, the accuracy of the model
depends on the quality and quantity of the training data from
different geographical areas. If the available data has an
imbalance (too much data from some areas and relatively little data
from other areas), the overall accuracy of the ML/AI model may be
decreased. In such cases, agents at network edge locations can be
instructed to identify UEs (using IMEI/IMSI) associated with users
who are highly mobile (step 240) and thus can provide data from
several different geographical areas. Location data from these UEs
is collected (step 242) and used as training data to refine the
location prediction model (step 244). The ML/AI model can then be
used to predict locations for UEs throughout the network coverage
area.
[0039] In an embodiment, the controller-collector agents can gather
the UE location information of persons who are likely to be highly
mobile (for example, Uber.RTM. drivers, Lyft.RTM. drivers) and thus
can provide diverse and dynamic data for training ML/AI models.
Location data of highly mobile users (users regularly traveling
through multiple cells of the network) can be used for a variety of
purposes (e.g., estimating road traffic and vehicle speed).
[0040] FIG. 2E depicts an illustrative embodiment of a method 205
in accordance with various aspects described herein. In step 2501,
collector-controller agents 2102 are instantiated at regional data
centers and network edges connected to a processing system. The
collector-controller agents monitor (step 2502) data transfers and
the status of databases (e.g., realtime database 2106) and
subsystems (e.g. data processing/streaming subsystems 2105), and
collect key performance indicators (KPIs) regarding the network.
Data 2503 obtained by the monitoring is used by controller 2103 to
assess available resources and the health of the system. The
controller also determines which data (or type of data) is to be
collected for a particular application (step 2504).
[0041] In this embodiment, the controller configures the streaming
sub-modules of the processing system (step 2506) and configures a
software defined network (SDN) to improve network performance (step
2508). The agents use a data collection algorithm to collect the
most informative data, based on the application (step 2510). The
collected data is stored in one or more real-time databases (step
2512); the data can be accessed by authorized/authenticated users
via a portal or a GUI.
[0042] While for purposes of simplicity of explanation, the
respective processes are shown and described as a series of blocks
in FIGS. 2B, 2D and 2E, it is to be understood and appreciated that
the claimed subject matter is not limited by the order of the
blocks, as some blocks may occur in different orders and/or
concurrently with other blocks from what is depicted and described
herein. Moreover, not all illustrated blocks may be required to
implement the methods described herein.
[0043] Referring now to FIG. 3, a block diagram 300 is shown
illustrating an example, non-limiting embodiment of a virtualized
communication network in accordance with various aspects described
herein. In particular a virtualized communication network is
presented that can be used to implement some or all of the
subsystems and functions of system 100, the subsystems and
functions of system 201, and method 205 presented in FIGS. 1, 2A,
2E, and 3. For example, virtualized communication network 300 can
facilitate in whole or in part operations including instantiating a
data collector agent at a network edge of the communication
network, where the data collector agent determines a type of data
to be collected for executing an application, determines a data
collection procedure including a data collection algorithm selected
in accordance with the application, and performs the data
collection procedure, resulting in collected data; the data
collection procedure can comprise selecting a subset from a set of
data items available to the data collector agent. The operations
can also include configuring a data processing module to process
the collected data in accordance with the application, where the
data processing module is connected to the data collector agent and
to a database, and comprises a data streaming system.
[0044] In particular, a cloud networking architecture is shown that
leverages cloud technologies and supports rapid innovation and
scalability via a transport layer 350, a virtualized network
function cloud 325 and/or one or more cloud computing environments
375. In various embodiments, this cloud networking architecture is
an open architecture that leverages application programming
interfaces (APIs); reduces complexity from services and operations;
supports more nimble business models; and rapidly and seamlessly
scales to meet evolving customer requirements including traffic
growth, diversity of traffic types, and diversity of performance
and reliability expectations.
[0045] In contrast to traditional network elements--which are
typically integrated to perform a single function, the virtualized
communication network employs virtual network elements (VNEs) 330,
332, 334, etc. that perform some or all of the functions of network
elements 150, 152, 154, 156, etc. For example, the network
architecture can provide a substrate of networking capability,
often called Network Function Virtualization Infrastructure (NFVI)
or simply infrastructure that is capable of being directed with
software and Software Defined Networking (SDN) protocols to perform
a broad variety of network functions and services. This
infrastructure can include several types of substrates. The most
typical type of substrate being servers that support Network
Function Virtualization (NFV), followed by packet forwarding
capabilities based on generic computing resources, with specialized
network technologies brought to bear when general purpose
processors or general purpose integrated circuit devices offered by
merchants (referred to herein as merchant silicon) are not
appropriate. In this case, communication services can be
implemented as cloud-centric workloads.
[0046] As an example, a traditional network element 150 (shown in
FIG. 1), such as an edge router can be implemented via a VNE 330
composed of NFV software modules, merchant silicon, and associated
controllers. The software can be written so that increasing
workload consumes incremental resources from a common resource
pool, and moreover so that it's elastic: so the resources are only
consumed when needed. In a similar fashion, other network elements
such as other routers, switches, edge caches, and middle-boxes are
instantiated from the common resource pool. Such sharing of
infrastructure across a broad set of uses makes planning and
growing infrastructure easier to manage.
[0047] In an embodiment, the transport layer 350 includes fiber,
cable, wired and/or wireless transport elements, network elements
and interfaces to provide broadband access 110, wireless access
120, voice access 130, media access 140 and/or access to content
sources 175 for distribution of content to any or all of the access
technologies. In particular, in some cases a network element needs
to be positioned at a specific place, and this allows for less
sharing of common infrastructure. Other times, the network elements
have specific physical layer adapters that cannot be abstracted or
virtualized, and might require special DSP code and analog
front-ends (AFEs) that do not lend themselves to implementation as
VNEs 330, 332 or 334. These network elements can be included in
transport layer 350.
[0048] The virtualized network function cloud 325 interfaces with
the transport layer 350 to provide the VNEs 330, 332, 334, etc. to
provide specific NFVs. In particular, the virtualized network
function cloud 325 leverages cloud operations, applications, and
architectures to support networking workloads. The virtualized
network elements 330, 332 and 334 can employ network function
software that provides either a one-for-one mapping of traditional
network element function or alternately some combination of network
functions designed for cloud computing. For example, VNEs 330, 332
and 334 can include route reflectors, domain name system (DNS)
servers, and dynamic host configuration protocol (DHCP) servers,
system architecture evolution (SAE) and/or mobility management
entity (MME) gateways, broadband network gateways, IP edge routers
for IP-VPN, Ethernet and other services, load balancers,
distributers and other network elements. Because these elements
don't typically need to forward large amounts of traffic, their
workload can be distributed across a number of servers--each of
which adds a portion of the capability, and overall which creates
an elastic function with higher availability than its former
monolithic version. These virtual network elements 330, 332, 334,
etc. can be instantiated and managed using an orchestration
approach similar to those used in cloud compute services.
[0049] The cloud computing environments 375 can interface with the
virtualized network function cloud 325 via APIs that expose
functional capabilities of the VNEs 330, 332, 334, etc. to provide
the flexible and expanded capabilities to the virtualized network
function cloud 325. In particular, network workloads may have
applications distributed across the virtualized network function
cloud 325 and cloud computing environment 375 and in the commercial
cloud, or might simply orchestrate workloads supported entirely in
NFV infrastructure from these third party locations.
[0050] Turning now to FIG. 4, there is illustrated a block diagram
of a computing environment in accordance with various aspects
described herein. In order to provide additional context for
various embodiments of the embodiments described herein, FIG. 4 and
the following discussion are intended to provide a brief, general
description of a suitable computing environment 400 in which the
various embodiments of the subject disclosure can be implemented.
In particular, computing environment 400 can be used in the
implementation of network elements 150, 152, 154, 156, access
terminal 112, base station or access point 122, switching device
132, media terminal 142, and/or VNEs 330, 332, 334, etc. Each of
these devices can be implemented via computer-executable
instructions that can run on one or more computers, and/or in
combination with other program modules and/or as a combination of
hardware and software. For example, computing environment 400 can
facilitate in whole or in part operations including instantiating a
data collector agent at a network edge of a communication network;
the data collector agent determines a type of data to be collected
for executing an application, determines a data collection
procedure including a data collection algorithm selected in
accordance with the application, and performs the data collection
procedure, resulting in collected data. The data collection
procedure can include selecting, from a set of data items available
to the data collector agent, a subset of the data items. The
operations can also include configuring a data processing module to
process the collected data in accordance with the application; the
data processing module is connected to the data collector agent and
to a database, and comprises a data streaming system.
[0051] Generally, program modules comprise routines, programs,
components, data structures, etc., that perform particular tasks or
implement particular abstract data types. Moreover, those skilled
in the art will appreciate that the methods can be practiced with
other computer system configurations, comprising single-processor
or multiprocessor computer systems, minicomputers, mainframe
computers, as well as personal computers, hand-held computing
devices, microprocessor-based or programmable consumer electronics,
and the like, each of which can be operatively coupled to one or
more associated devices.
[0052] As used herein, a processing circuit includes one or more
processors as well as other application specific circuits such as
an application specific integrated circuit, digital logic circuit,
state machine, programmable gate array or other circuit that
processes input signals or data and that produces output signals or
data in response thereto. It should be noted that while any
functions and features described herein in association with the
operation of a processor could likewise be performed by a
processing circuit.
[0053] The illustrated embodiments of the embodiments herein can be
also practiced in distributed computing environments where certain
tasks are performed by remote processing devices that are linked
through a communications network. In a distributed computing
environment, program modules can be located in both local and
remote memory storage devices.
[0054] Computing devices typically comprise a variety of media,
which can comprise computer-readable storage media and/or
communications media, which two terms are used herein differently
from one another as follows. Computer-readable storage media can be
any available storage media that can be accessed by the computer
and comprises both volatile and nonvolatile media, removable and
non-removable media. By way of example, and not limitation,
computer-readable storage media can be implemented in connection
with any method or technology for storage of information such as
computer-readable instructions, program modules, structured data or
unstructured data.
[0055] Computer-readable storage media can comprise, but are not
limited to, random access memory (RAM), read only memory (ROM),
electrically erasable programmable read only memory (EEPROM), flash
memory or other memory technology, compact disk read only memory
(CD-ROM), digital versatile disk (DVD) or other optical disk
storage, magnetic cassettes, magnetic tape, magnetic disk storage
or other magnetic storage devices or other tangible and/or
non-transitory media which can be used to store desired
information. In this regard, the terms "tangible" or
"non-transitory" herein as applied to storage, memory or
computer-readable media, are to be understood to exclude only
propagating transitory signals per se as modifiers and do not
relinquish rights to all standard storage, memory or
computer-readable media that are not only propagating transitory
signals per se.
[0056] Computer-readable storage media can be accessed by one or
more local or remote computing devices, e.g., via access requests,
queries or other data retrieval protocols, for a variety of
operations with respect to the information stored by the
medium.
[0057] Communications media typically embody computer-readable
instructions, data structures, program modules or other structured
or unstructured data in a data signal such as a modulated data
signal, e.g., a carrier wave or other transport mechanism, and
comprises any information delivery or transport media. The term
"modulated data signal" or signals refers to a signal that has one
or more of its characteristics set or changed in such a manner as
to encode information in one or more signals. By way of example,
and not limitation, communication media comprise wired media, such
as a wired network or direct-wired connection, and wireless media
such as acoustic, RF, infrared and other wireless media.
[0058] With reference again to FIG. 4, the example environment can
comprise a computer 402, the computer 402 comprising a processing
unit 404, a system memory 406 and a system bus 408. The system bus
408 couples system components including, but not limited to, the
system memory 406 to the processing unit 404. The processing unit
404 can be any of various commercially available processors. Dual
microprocessors and other multiprocessor architectures can also be
employed as the processing unit 404.
[0059] The system bus 408 can be any of several types of bus
structure that can further interconnect to a memory bus (with or
without a memory controller), a peripheral bus, and a local bus
using any of a variety of commercially available bus architectures.
The system memory 406 comprises ROM 410 and RAM 412. A basic
input/output system (BIOS) can be stored in a non-volatile memory
such as ROM, erasable programmable read only memory (EPROM),
EEPROM, which BIOS contains the basic routines that help to
transfer information between elements within the computer 402, such
as during startup. The RAM 412 can also comprise a high-speed RAM
such as static RAM for caching data.
[0060] The computer 402 further comprises an internal hard disk
drive (HDD) 414 (e.g., EIDE, SATA), which internal HDD 414 can also
be configured for external use in a suitable chassis (not shown), a
magnetic floppy disk drive (FDD) 416, (e.g., to read from or write
to a removable diskette 418) and an optical disk drive 420, (e.g.,
reading a CD-ROM disk 422 or, to read from or write to other high
capacity optical media such as the DVD). The HDD 414, magnetic FDD
416 and optical disk drive 420 can be connected to the system bus
408 by a hard disk drive interface 424, a magnetic disk drive
interface 426 and an optical drive interface 428, respectively. The
hard disk drive interface 424 for external drive implementations
comprises at least one or both of Universal Serial Bus (USB) and
Institute of Electrical and Electronics Engineers (IEEE) 1394
interface technologies. Other external drive connection
technologies are within contemplation of the embodiments described
herein.
[0061] The drives and their associated computer-readable storage
media provide nonvolatile storage of data, data structures,
computer-executable instructions, and so forth. For the computer
402, the drives and storage media accommodate the storage of any
data in a suitable digital format. Although the description of
computer-readable storage media above refers to a hard disk drive
(HDD), a removable magnetic diskette, and a removable optical media
such as a CD or DVD, it should be appreciated by those skilled in
the art that other types of storage media which are readable by a
computer, such as zip drives, magnetic cassettes, flash memory
cards, cartridges, and the like, can also be used in the example
operating environment, and further, that any such storage media can
contain computer-executable instructions for performing the methods
described herein.
[0062] A number of program modules can be stored in the drives and
RAM 412, comprising an operating system 430, one or more
application programs 432, other program modules 434 and program
data 436. All or portions of the operating system, applications,
modules, and/or data can also be cached in the RAM 412. The systems
and methods described herein can be implemented utilizing various
commercially available operating systems or combinations of
operating systems.
[0063] A user can enter commands and information into the computer
402 through one or more wired/wireless input devices, e.g., a
keyboard 438 and a pointing device, such as a mouse 440. Other
input devices (not shown) can comprise a microphone, an infrared
(IR) remote control, a joystick, a game pad, a stylus pen, touch
screen or the like. These and other input devices are often
connected to the processing unit 404 through an input device
interface 442 that can be coupled to the system bus 408, but can be
connected by other interfaces, such as a parallel port, an IEEE
1394 serial port, a game port, a universal serial bus (USB) port,
an IR interface, etc.
[0064] A monitor 444 or other type of display device can be also
connected to the system bus 408 via an interface, such as a video
adapter 446. It will also be appreciated that in alternative
embodiments, a monitor 444 can also be any display device (e.g.,
another computer having a display, a smart phone, a tablet
computer, etc.) for receiving display information associated with
computer 402 via any communication means, including via the
Internet and cloud-based networks. In addition to the monitor 444,
a computer typically comprises other peripheral output devices (not
shown), such as speakers, printers, etc.
[0065] The computer 402 can operate in a networked environment
using logical connections via wired and/or wireless communications
to one or more remote computers, such as a remote computer(s) 448.
The remote computer(s) 448 can be a workstation, a server computer,
a router, a personal computer, portable computer,
microprocessor-based entertainment appliance, a peer device or
other common network node, and typically comprises many or all of
the elements described relative to the computer 402, although, for
purposes of brevity, only a remote memory/storage device 450 is
illustrated. The logical connections depicted comprise
wired/wireless connectivity to a local area network (LAN) 452
and/or larger networks, e.g., a wide area network (WAN) 454. Such
LAN and WAN networking environments are commonplace in offices and
companies, and facilitate enterprise-wide computer networks, such
as intranets, all of which can connect to a global communications
network, e.g., the Internet.
[0066] When used in a LAN networking environment, the computer 402
can be connected to the LAN 452 through a wired and/or wireless
communication network interface or adapter 456. The adapter 456 can
facilitate wired or wireless communication to the LAN 452, which
can also comprise a wireless AP disposed thereon for communicating
with the adapter 456.
[0067] When used in a WAN networking environment, the computer 402
can comprise a modem 458 or can be connected to a communications
server on the WAN 454 or has other means for establishing
communications over the WAN 454, such as by way of the Internet.
The modem 458, which can be internal or external and a wired or
wireless device, can be connected to the system bus 408 via the
input device interface 442. In a networked environment, program
modules depicted relative to the computer 402 or portions thereof,
can be stored in the remote memory/storage device 450. It will be
appreciated that the network connections shown are example and
other means of establishing a communications link between the
computers can be used.
[0068] The computer 402 can be operable to communicate with any
wireless devices or entities operatively disposed in wireless
communication, e.g., a printer, scanner, desktop and/or portable
computer, portable data assistant, communications satellite, any
piece of equipment or location associated with a wirelessly
detectable tag (e.g., a kiosk, news stand, restroom), and
telephone. This can comprise Wireless Fidelity (Wi-Fi) and
BLUETOOTH.RTM. wireless technologies. Thus, the communication can
be a predefined structure as with a conventional network or simply
an ad hoc communication between at least two devices.
[0069] Wi-Fi can allow connection to the Internet from a couch at
home, a bed in a hotel room or a conference room at work, without
wires. Wi-Fi is a wireless technology similar to that used in a
cell phone that enables such devices, e.g., computers, to send and
receive data indoors and out; anywhere within the range of a base
station. Wi-Fi networks use radio technologies called IEEE 802.11
(a, b, g, n, ac, ag, etc.) to provide secure, reliable, fast
wireless connectivity. A Wi-Fi network can be used to connect
computers to each other, to the Internet, and to wired networks
(which can use IEEE 802.3 or Ethernet). Wi-Fi networks operate in
the unlicensed 2.4 and 5 GHz radio bands for example or with
products that contain both bands (dual band), so the networks can
provide real-world performance similar to the basic 10BaseT wired
Ethernet networks used in many offices.
[0070] Turning now to FIG. 5, an embodiment 500 of a mobile network
platform 510 is shown that is an example of network elements 150,
152, 154, 156, and/or VNEs 330, 332, 334, etc. For example,
platform 510 can facilitate in whole or in part operations
including instantiating a data collector agent at a network edge of
a communication network; the data collector agent determines a type
of data to be collected for executing an application, determines a
data collection procedure including a data collection algorithm
selected in accordance with the application, and performs the data
collection procedure, resulting in collected data. The data
collection procedure can include selecting, from a set of data
items available to the data collector agent, a subset of the data
items. The operations can also include configuring a data
processing module to process the collected data in accordance with
the application; the data processing module is connected to the
data collector agent and to a database, and comprises a data
streaming system.
[0071] In one or more embodiments, the mobile network platform 510
can generate and receive signals transmitted and received by base
stations or access points such as base station or access point 122.
Generally, mobile network platform 510 can comprise components,
e.g., nodes, gateways, interfaces, servers, or disparate platforms,
that facilitate both packet-switched (PS) (e.g., internet protocol
(IP), frame relay, asynchronous transfer mode (ATM)) and
circuit-switched (CS) traffic (e.g., voice and data), as well as
control generation for networked wireless telecommunication. As a
non-limiting example, mobile network platform 510 can be included
in telecommunications carrier networks, and can be considered
carrier-side components as discussed elsewhere herein. Mobile
network platform 510 comprises CS gateway node(s) 512 which can
interface CS traffic received from legacy networks like telephony
network(s) 540 (e.g., public switched telephone network (PSTN), or
public land mobile network (PLMN)) or a signaling system #7 (SS7)
network 560. CS gateway node(s) 512 can authorize and authenticate
traffic (e.g., voice) arising from such networks. Additionally, CS
gateway node(s) 512 can access mobility, or roaming, data generated
through SS7 network 560; for instance, mobility data stored in a
visited location register (VLR), which can reside in memory 530.
Moreover, CS gateway node(s) 512 interfaces CS-based traffic and
signaling and PS gateway node(s) 518. As an example, in a 3GPP UMTS
network, CS gateway node(s) 512 can be realized at least in part in
gateway GPRS support node(s) (GGSN). It should be appreciated that
functionality and specific operation of CS gateway node(s) 512, PS
gateway node(s) 518, and serving node(s) 516, is provided and
dictated by radio technology(ies) utilized by mobile network
platform 510 for telecommunication over a radio access network 520
with other devices, such as a radiotelephone 575.
[0072] In addition to receiving and processing CS-switched traffic
and signaling, PS gateway node(s) 518 can authorize and
authenticate PS-based data sessions with served mobile devices.
Data sessions can comprise traffic, or content(s), exchanged with
networks external to the mobile network platform 510, like wide
area network(s) (WANs) 550, enterprise network(s) 570, and service
network(s) 580, which can be embodied in local area network(s)
(LANs), can also be interfaced with mobile network platform 510
through PS gateway node(s) 518. It is to be noted that WANs 550 and
enterprise network(s) 570 can embody, at least in part, a service
network(s) like IP multimedia subsystem (IMS). Based on radio
technology layer(s) available in technology resource(s) or radio
access network 520, PS gateway node(s) 518 can generate packet data
protocol contexts when a data session is established; other data
structures that facilitate routing of packetized data also can be
generated. To that end, in an aspect, PS gateway node(s) 518 can
comprise a tunnel interface (e.g., tunnel termination gateway (TTG)
in 3GPP UMTS network(s) (not shown)) which can facilitate
packetized communication with disparate wireless network(s), such
as Wi-Fi networks.
[0073] In embodiment 500, mobile network platform 510 also
comprises serving node(s) 516 that, based upon available radio
technology layer(s) within technology resource(s) in the radio
access network 520, convey the various packetized flows of data
streams received through PS gateway node(s) 518. It is to be noted
that for technology resource(s) that rely primarily on CS
communication, server node(s) can deliver traffic without reliance
on PS gateway node(s) 518; for example, server node(s) can embody
at least in part a mobile switching center. As an example, in a
3GPP UMTS network, serving node(s) 516 can be embodied in serving
GPRS support node(s) (SGSN).
[0074] For radio technologies that exploit packetized
communication, server(s) 514 in mobile network platform 510 can
execute numerous applications that can generate multiple disparate
packetized data streams or flows, and manage (e.g., schedule,
queue, format . . . ) such flows. Such application(s) can comprise
add-on features to standard services (for example, provisioning,
billing, customer support . . . ) provided by mobile network
platform 510. Data streams (e.g., content(s) that are part of a
voice call or data session) can be conveyed to PS gateway node(s)
518 for authorization/authentication and initiation of a data
session, and to serving node(s) 516 for communication thereafter.
In addition to application server, server(s) 514 can comprise
utility server(s), a utility server can comprise a provisioning
server, an operations and maintenance server, a security server
that can implement at least in part a certificate authority and
firewalls as well as other security mechanisms, and the like. In an
aspect, security server(s) secure communication served through
mobile network platform 510 to ensure network's operation and data
integrity in addition to authorization and authentication
procedures that CS gateway node(s) 512 and PS gateway node(s) 518
can enact. Moreover, provisioning server(s) can provision services
from external network(s) like networks operated by a disparate
service provider; for instance, WAN 550 or Global Positioning
System (GPS) network(s) (not shown). Provisioning server(s) can
also provision coverage through networks associated to mobile
network platform 510 (e.g., deployed and operated by the same
service provider), such as the distributed antennas networks shown
in FIG. 1(s) that enhance wireless service coverage by providing
more network coverage.
[0075] It is to be noted that server(s) 514 can comprise one or
more processors configured to confer at least in part the
functionality of mobile network platform 510. To that end, the one
or more processor can execute code instructions stored in memory
530, for example. It is should be appreciated that server(s) 514
can comprise a content manager, which operates in substantially the
same manner as described hereinbefore.
[0076] In example embodiment 500, memory 530 can store information
related to operation of mobile network platform 510. Other
operational information can comprise provisioning information of
mobile devices served through mobile network platform 510,
subscriber databases; application intelligence, pricing schemes,
e.g., promotional rates, flat-rate programs, couponing campaigns;
technical specification(s) consistent with telecommunication
protocols for operation of disparate radio, or wireless, technology
layers; and so forth. Memory 530 can also store information from at
least one of telephony network(s) 540, WAN 550, SS7 network 560, or
enterprise network(s) 570. In an aspect, memory 530 can be, for
example, accessed as part of a data store component or as a
remotely connected memory store.
[0077] In order to provide a context for the various aspects of the
disclosed subject matter, FIG. 5, and the following discussion, are
intended to provide a brief, general description of a suitable
environment in which the various aspects of the disclosed subject
matter can be implemented. While the subject matter has been
described above in the general context of computer-executable
instructions of a computer program that runs on a computer and/or
computers, those skilled in the art will recognize that the
disclosed subject matter also can be implemented in combination
with other program modules. Generally, program modules comprise
routines, programs, components, data structures, etc. that perform
particular tasks and/or implement particular abstract data
types.
[0078] Turning now to FIG. 6, an illustrative embodiment of a
communication device 600 is shown. The communication device 600 can
serve as an illustrative embodiment of devices such as data
terminals 114, mobile devices 124, vehicle 126, display devices 144
or other client devices for communication via either communications
network 125. For example, computing device 600 can facilitate in
whole or in part operations including instantiating a data
collector agent at a network edge of a communication network; the
data collector agent determines a type of data to be collected for
executing an application, determines a data collection procedure
including a data collection algorithm selected in accordance with
the application, and performs the data collection procedure,
resulting in collected data. The data collection procedure can
include selecting, from a set of data items available to the data
collector agent, a subset of the data items. The operations can
also include configuring a data processing module to process the
collected data in accordance with the application; the data
processing module is connected to the data collector agent and to a
database, and comprises a data streaming system.
[0079] The communication device 600 can comprise a wireline and/or
wireless transceiver 602 (herein transceiver 602), a user interface
(UI) 604, a power supply 614, a location receiver 616, a motion
sensor 618, an orientation sensor 620, and a controller 606 for
managing operations thereof. The transceiver 602 can support
short-range or long-range wireless access technologies such as
Bluetooth.RTM., ZigBee.RTM., WiFi, DECT, or cellular communication
technologies, just to mention a few (Bluetooth.RTM. and ZigBee.RTM.
are trademarks registered by the Bluetooth.RTM. Special Interest
Group and the ZigBee.RTM. Alliance, respectively). Cellular
technologies can include, for example, CDMA-1X, UMTS/HSDPA,
GSM/GPRS, TDMA/EDGE, EV/DO, WiMAX, SDR, LTE, as well as other next
generation wireless communication technologies as they arise. The
transceiver 602 can also be adapted to support circuit-switched
wireline access technologies (such as PSTN), packet-switched
wireline access technologies (such as TCP/IP, VoIP, etc.), and
combinations thereof.
[0080] The UI 604 can include a depressible or touch-sensitive
keypad 608 with a navigation mechanism such as a roller ball, a
joystick, a mouse, or a navigation disk for manipulating operations
of the communication device 600. The keypad 608 can be an integral
part of a housing assembly of the communication device 600 or an
independent device operably coupled thereto by a tethered wireline
interface (such as a USB cable) or a wireless interface supporting
for example Bluetooth.RTM.. The keypad 608 can represent a numeric
keypad commonly used by phones, and/or a QWERTY keypad with
alphanumeric keys. The UI 604 can further include a display 610
such as monochrome or color LCD (Liquid Crystal Display), OLED
(Organic Light Emitting Diode) or other suitable display technology
for conveying images to an end user of the communication device
600. In an embodiment where the display 610 is touch-sensitive, a
portion or all of the keypad 608 can be presented by way of the
display 610 with navigation features.
[0081] The display 610 can use touch screen technology to also
serve as a user interface for detecting user input. As a touch
screen display, the communication device 600 can be adapted to
present a user interface having graphical user interface (GUI)
elements that can be selected by a user with a touch of a finger.
The display 610 can be equipped with capacitive, resistive or other
forms of sensing technology to detect how much surface area of a
user's finger has been placed on a portion of the touch screen
display. This sensing information can be used to control the
manipulation of the GUI elements or other functions of the user
interface. The display 610 can be an integral part of the housing
assembly of the communication device 600 or an independent device
communicatively coupled thereto by a tethered wireline interface
(such as a cable) or a wireless interface.
[0082] The UI 604 can also include an audio system 612 that
utilizes audio technology for conveying low volume audio (such as
audio heard in proximity of a human ear) and high volume audio
(such as speakerphone for hands free operation). The audio system
612 can further include a microphone for receiving audible signals
of an end user. The audio system 612 can also be used for voice
recognition applications. The UI 604 can further include an image
sensor 613 such as a charged coupled device (CCD) camera for
capturing still or moving images.
[0083] The power supply 614 can utilize common power management
technologies such as replaceable and rechargeable batteries, supply
regulation technologies, and/or charging system technologies for
supplying energy to the components of the communication device 600
to facilitate long-range or short-range portable communications.
Alternatively, or in combination, the charging system can utilize
external power sources such as DC power supplied over a physical
interface such as a USB port or other suitable tethering
technologies.
[0084] The location receiver 616 can utilize location technology
such as a global positioning system (GPS) receiver capable of
assisted GPS for identifying a location of the communication device
600 based on signals generated by a constellation of GPS
satellites, which can be used for facilitating location services
such as navigation. The motion sensor 618 can utilize motion
sensing technology such as an accelerometer, a gyroscope, or other
suitable motion sensing technology to detect motion of the
communication device 600 in three-dimensional space. The
orientation sensor 620 can utilize orientation sensing technology
such as a magnetometer to detect the orientation of the
communication device 600 (north, south, west, and east, as well as
combined orientations in degrees, minutes, or other suitable
orientation metrics).
[0085] The communication device 600 can use the transceiver 602 to
also determine a proximity to a cellular, WiFi, Bluetooth.RTM., or
other wireless access points by sensing techniques such as
utilizing a received signal strength indicator (RSSI) and/or signal
time of arrival (TOA) or time of flight (TOF) measurements. The
controller 606 can utilize computing technologies such as a
microprocessor, a digital signal processor (DSP), programmable gate
arrays, application specific integrated circuits, and/or a video
processor with associated storage memory such as Flash, ROM, RAM,
SRAM, DRAM or other storage technologies for executing computer
instructions, controlling, and processing data supplied by the
aforementioned components of the communication device 600.
[0086] Other components not shown in FIG. 6 can be used in one or
more embodiments of the subject disclosure. For instance, the
communication device 600 can include a slot for adding or removing
an identity module such as a Subscriber Identity Module (SIM) card
or Universal Integrated Circuit Card (UICC). SIM or UICC cards can
be used for identifying subscriber services, executing programs,
storing subscriber data, and so on.
[0087] The terms "first," "second," "third," and so forth, as used
in the claims, unless otherwise clear by context, is for clarity
only and doesn't otherwise indicate or imply any order in time. For
instance, "a first determination," "a second determination," and "a
third determination," does not indicate or imply that the first
determination is to be made before the second determination, or
vice versa, etc.
[0088] In the subject specification, terms such as "store,"
"storage," "data store," data storage," "database," and
substantially any other information storage component relevant to
operation and functionality of a component, refer to "memory
components," or entities embodied in a "memory" or components
comprising the memory. It will be appreciated that the memory
components described herein can be either volatile memory or
nonvolatile memory, or can comprise both volatile and nonvolatile
memory, by way of illustration, and not limitation, volatile
memory, non-volatile memory, disk storage, and memory storage.
Further, nonvolatile memory can be included in read only memory
(ROM), programmable ROM (PROM), electrically programmable ROM
(EPROM), electrically erasable ROM (EEPROM), or flash memory.
Volatile memory can comprise random access memory (RAM), which acts
as external cache memory. By way of illustration and not
limitation, RAM is available in many forms such as synchronous RAM
(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data
rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM
(SLDRAM), and direct Rambus RAM (DRRAM). Additionally, the
disclosed memory components of systems or methods herein are
intended to comprise, without being limited to comprising, these
and any other suitable types of memory.
[0089] Moreover, it will be noted that the disclosed subject matter
can be practiced with other computer system configurations,
comprising single-processor or multiprocessor computer systems,
mini-computing devices, mainframe computers, as well as personal
computers, hand-held computing devices (e.g., PDA, phone,
smartphone, watch, tablet computers, netbook computers, etc.),
microprocessor-based or programmable consumer or industrial
electronics, and the like. The illustrated aspects can also be
practiced in distributed computing environments where tasks are
performed by remote processing devices that are linked through a
communications network; however, some if not all aspects of the
subject disclosure can be practiced on stand-alone computers. In a
distributed computing environment, program modules can be located
in both local and remote memory storage devices.
[0090] In one or more embodiments, information regarding use of
services can be generated including services being accessed, media
consumption history, user preferences, and so forth. This
information can be obtained by various methods including user
input, detecting types of communications (e.g., video content vs.
audio content), analysis of content streams, sampling, and so
forth. The generating, obtaining and/or monitoring of this
information can be responsive to an authorization provided by the
user. In one or more embodiments, an analysis of data can be
subject to authorization from user(s) associated with the data,
such as an opt-in, an opt-out, acknowledgement requirements,
notifications, selective authorization based on types of data, and
so forth.
[0091] Some of the embodiments described herein can also employ
artificial intelligence (AI) to facilitate automating one or more
features described herein. The embodiments (e.g., in connection
with automatically identifying acquired cell sites that provide a
maximum value/benefit after addition to an existing communication
network) can employ various AI-based schemes for carrying out
various embodiments thereof. Moreover, the classifier can be
employed to determine a ranking or priority of each cell site of
the acquired network. A classifier is a function that maps an input
attribute vector, x=(x1, x2, x3, x4, . . . , xn), to a confidence
that the input belongs to a class, that is, f(x)=confidence
(class). Such classification can employ a probabilistic and/or
statistical-based analysis (e.g., factoring into the analysis
utilities and costs) to determine or infer an action that a user
desires to be automatically performed. A support vector machine
(SVM) is an example of a classifier that can be employed. The SVM
operates by finding a hypersurface in the space of possible inputs,
which the hypersurface attempts to split the triggering criteria
from the non-triggering events. Intuitively, this makes the
classification correct for testing data that is near, but not
identical to training data. Other directed and undirected model
classification approaches comprise, e.g., naive Bayes, Bayesian
networks, decision trees, neural networks, fuzzy logic models, and
probabilistic classification models providing different patterns of
independence can be employed. Classification as used herein also is
inclusive of statistical regression that is utilized to develop
models of priority.
[0092] As will be readily appreciated, one or more of the
embodiments can employ classifiers that are explicitly trained
(e.g., via a generic training data) as well as implicitly trained
(e.g., via observing UE behavior, operator preferences, historical
information, receiving extrinsic information). For example, SVMs
can be configured via a learning or training phase within a
classifier constructor and feature selection module. Thus, the
classifier(s) can be used to automatically learn and perform a
number of functions, including but not limited to determining
according to predetermined criteria which of the acquired cell
sites will benefit a maximum number of subscribers and/or which of
the acquired cell sites will add minimum value to the existing
communication network coverage, etc.
[0093] As used in some contexts in this application, in some
embodiments, the terms "component," "system" and the like are
intended to refer to, or comprise, a computer-related entity or an
entity related to an operational apparatus with one or more
specific functionalities, wherein the entity can be either
hardware, a combination of hardware and software, software, or
software in execution. As an example, a component may be, but is
not limited to being, a process running on a processor, a
processor, an object, an executable, a thread of execution,
computer-executable instructions, a program, and/or a computer. By
way of illustration and not limitation, both an application running
on a server and the server can be a component. One or more
components may reside within a process and/or thread of execution
and a component may be localized on one computer and/or distributed
between two or more computers. In addition, these components can
execute from various computer readable media having various data
structures stored thereon. The components may communicate via local
and/or remote processes such as in accordance with a signal having
one or more data packets (e.g., data from one component interacting
with another component in a local system, distributed system,
and/or across a network such as the Internet with other systems via
the signal). As another example, a component can be an apparatus
with specific functionality provided by mechanical parts operated
by electric or electronic circuitry, which is operated by a
software or firmware application executed by a processor, wherein
the processor can be internal or external to the apparatus and
executes at least a part of the software or firmware application.
As yet another example, a component can be an apparatus that
provides specific functionality through electronic components
without mechanical parts, the electronic components can comprise a
processor therein to execute software or firmware that confers at
least in part the functionality of the electronic components. While
various components have been illustrated as separate components, it
will be appreciated that multiple components can be implemented as
a single component, or a single component can be implemented as
multiple components, without departing from example
embodiments.
[0094] Further, the various embodiments can be implemented as a
method, apparatus or article of manufacture using standard
programming and/or engineering techniques to produce software,
firmware, hardware or any combination thereof to control a computer
to implement the disclosed subject matter. The term "article of
manufacture" as used herein is intended to encompass a computer
program accessible from any computer-readable device or
computer-readable storage/communications media. For example,
computer readable storage media can include, but are not limited
to, magnetic storage devices (e.g., hard disk, floppy disk,
magnetic strips), optical disks (e.g., compact disk (CD), digital
versatile disk (DVD)), smart cards, and flash memory devices (e.g.,
card, stick, key drive). Of course, those skilled in the art will
recognize many modifications can be made to this configuration
without departing from the scope or spirit of the various
embodiments.
[0095] In addition, the words "example" and "exemplary" are used
herein to mean serving as an instance or illustration. Any
embodiment or design described herein as "example" or "exemplary"
is not necessarily to be construed as preferred or advantageous
over other embodiments or designs. Rather, use of the word example
or exemplary is intended to present concepts in a concrete fashion.
As used in this application, the term "or" is intended to mean an
inclusive "or" rather than an exclusive "or". That is, unless
specified otherwise or clear from context, "X employs A or B" is
intended to mean any of the natural inclusive permutations. That
is, if X employs A; X employs B; or X employs both A and B, then "X
employs A or B" is satisfied under any of the foregoing instances.
In addition, the articles "a" and "an" as used in this application
and the appended claims should generally be construed to mean "one
or more" unless specified otherwise or clear from context to be
directed to a singular form.
[0096] Moreover, terms such as "user equipment," "mobile station,"
"mobile," subscriber station," "access terminal," "terminal,"
"handset," "mobile device" (and/or terms representing similar
terminology) can refer to a wireless device utilized by a
subscriber or user of a wireless communication service to receive
or convey data, control, voice, video, sound, gaming or
substantially any data-stream or signaling-stream. The foregoing
terms are utilized interchangeably herein and with reference to the
related drawings.
[0097] Furthermore, the terms "user," "subscriber," "customer,"
"consumer" and the like are employed interchangeably throughout,
unless context warrants particular distinctions among the terms. It
should be appreciated that such terms can refer to human entities
or automated components supported through artificial intelligence
(e.g., a capacity to make inference based, at least, on complex
mathematical formalisms), which can provide simulated vision, sound
recognition and so forth.
[0098] As employed herein, the term "processor" can refer to
substantially any computing processing unit or device comprising,
but not limited to comprising, single-core processors;
single-processors with software multithread execution capability;
multi-core processors; multi-core processors with software
multithread execution capability; multi-core processors with
hardware multithread technology; parallel platforms; and parallel
platforms with distributed shared memory. Additionally, a processor
can refer to an integrated circuit, an application specific
integrated circuit (ASIC), a digital signal processor (DSP), a
field programmable gate array (FPGA), a programmable logic
controller (PLC), a complex programmable logic device (CPLD), a
discrete gate or transistor logic, discrete hardware components or
any combination thereof designed to perform the functions described
herein. Processors can exploit nano-scale architectures such as,
but not limited to, molecular and quantum-dot based transistors,
switches and gates, in order to optimize space usage or enhance
performance of user equipment. A processor can also be implemented
as a combination of computing processing units.
[0099] As used herein, terms such as "data storage," data storage,"
"database," and substantially any other information storage
component relevant to operation and functionality of a component,
refer to "memory components," or entities embodied in a "memory" or
components comprising the memory. It will be appreciated that the
memory components or computer-readable storage media, described
herein can be either volatile memory or nonvolatile memory or can
include both volatile and nonvolatile memory.
[0100] What has been described above includes mere examples of
various embodiments. It is, of course, not possible to describe
every conceivable combination of components or methodologies for
purposes of describing these examples, but one of ordinary skill in
the art can recognize that many further combinations and
permutations of the present embodiments are possible. Accordingly,
the embodiments disclosed and/or claimed herein are intended to
embrace all such alterations, modifications and variations that
fall within the spirit and scope of the appended claims.
Furthermore, to the extent that the term "includes" is used in
either the detailed description or the claims, such term is
intended to be inclusive in a manner similar to the term
"comprising" as "comprising" is interpreted when employed as a
transitional word in a claim.
[0101] In addition, a flow diagram may include a "start" and/or
"continue" indication. The "start" and "continue" indications
reflect that the steps presented can optionally be incorporated in
or otherwise used in conjunction with other routines. In this
context, "start" indicates the beginning of the first step
presented and may be preceded by other activities not specifically
shown. Further, the "continue" indication reflects that the steps
presented may be performed multiple times and/or may be succeeded
by other activities not specifically shown. Further, while a flow
diagram indicates a particular ordering of steps, other orderings
are likewise possible provided that the principles of causality are
maintained.
[0102] As may also be used herein, the term(s) "operably coupled
to", "coupled to", and/or "coupling" includes direct coupling
between items and/or indirect coupling between items via one or
more intervening items. Such items and intervening items include,
but are not limited to, junctions, communication paths, components,
circuit elements, circuits, functional blocks, and/or devices. As
an example of indirect coupling, a signal conveyed from a first
item to a second item may be modified by one or more intervening
items by modifying the form, nature or format of information in a
signal, while one or more elements of the information in the signal
are nevertheless conveyed in a manner than can be recognized by the
second item. In a further example of indirect coupling, an action
in a first item can cause a reaction on the second item, as a
result of actions and/or reactions in one or more intervening
items.
[0103] Although specific embodiments have been illustrated and
described herein, it should be appreciated that any arrangement
which achieves the same or similar purpose may be substituted for
the embodiments described or shown by the subject disclosure. The
subject disclosure is intended to cover any and all adaptations or
variations of various embodiments. Combinations of the above
embodiments, and other embodiments not specifically described
herein, can be used in the subject disclosure. For instance, one or
more features from one or more embodiments can be combined with one
or more features of one or more other embodiments. In one or more
embodiments, features that are positively recited can also be
negatively recited and excluded from the embodiment with or without
replacement by another structural and/or functional feature. The
steps or functions described with respect to the embodiments of the
subject disclosure can be performed in any order. The steps or
functions described with respect to the embodiments of the subject
disclosure can be performed alone or in combination with other
steps or functions of the subject disclosure, as well as from other
embodiments or from other steps that have not been described in the
subject disclosure. Further, more than or less than all of the
features described with respect to an embodiment can also be
utilized.
* * * * *